polars
A fast DataFrame library implemented in Rust with a Python API.
- Status
- Generally available
- Last checked
- Checked · Oct 16, 2026
- License
- Open source
- Pricing
- Free tier · from $0
What it is
Polars is a high-performance DataFrame library written in Rust that provides a Python API for efficient data manipulation and analysis. It is designed to handle large datasets quickly, making it ideal for data-intensive applications.
Polars stands out as a high-performance DataFrame library written in Rust, offering efficient memory management and fast operations, making it ideal for developers who need speed and efficiency.
When it fits — and when it doesn’t
A good fit for
Developers working with Python who need high-performance DataFrame operations
Projects requiring efficient memory usage and fast data manipulation
Applications that process large volumes of data in real-time
Look elsewhere if
Teams needing a web-based UI for data analysis (polars is a library)
Projects where the primary language is not Python or Rust
Known weaknesses
Each one links to the public issue, changelog or docs page it came from, where we have one.
- 01
Limited language support beyond Python and Rust
Primary API is in Python with a Rust backend; other languages have limited or no official support
- 02
Complex setup for non-standard environments
Requires specific versions of dependencies and can be challenging to integrate into existing complex systems
What it does well
High-performance data manipulation and analysis
Efficient memory management
Support for lazy evaluation to optimize performance
Wide range of operations including filtering, grouping, and joining
Pricing
- Free tier
- YesOpen source — free to use
- Paid from
- $0
- Model
- Flat rate
- Enterprise plan
- No
Pricing not independently confirmed — check the vendor’s page.
Performance benchmarks
How Fast Is It?
Set up polars
Setup steps, common gotchas and what to check after 30 days.